Luca Talent · 1 month ago
Machine Learning Engineer – Gurobi Scheduling Optimization (Hybrid)
Los Angeles|Irvine, CA|San Diego
Full-time
Hybrid
Mid, Senior Level
$75/hr - $95/hrLuca Talent is seeking a Machine Learning Engineer to take ownership of a new AI scheduling engine designed to optimize scheduling for over 1 million employees worldwide. The role involves designing and implementing optimization models, integrating machine learning with optimization, and developing scalable systems in a collaborative environment.
Human ResourcesProfessional ServicesRecruitingStaffing Agency
No H1B
U.S. Citizen Only
Responsibilities
Build the Core Optimization Engine: Design and implement robust optimization models using Gurobi, CPLEX, OR-Tools, or similar solvers
Model Real-World Complexity: Translate intricate scheduling rules — labor laws, coverage, shift constraints — into elegant, scalable mathematical formulations
Integrate AI & Forecasting: Combine machine learning predictions with optimization models to create smarter, adaptive scheduling recommendations
Engineer for Scale: Develop modular, production-grade systems in Python, with SQL and AWS for large-scale data processing and deployment
Collaborate & Innovate: Work with a cross-functional, startup-minded team to continuously refine models, improve performance, and push the boundaries of AI scheduling
Qualification
Required
Hands-on experience designing and implementing optimization or constraint-based systems using Gurobi or similar tools
Strong proficiency in Python and SQL
Background in machine learning, forecasting, or hybrid optimization approaches
Solid understanding of algorithms, operations research, or scheduling constraints
Familiarity with CI/CD, Docker, and cloud deployments (AWS)
Preferred
Experience in workforce scheduling or resource optimization at scale
Bachelor's or Master's in Computer Science, Operations Research, or Applied Mathematics
Company
Luca Talent
Luca Talent is a boutique technology staffing firm that focuses on contingent and temporary staffing in the technology sector.
Founded in 2014
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase